{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Author: Sebastian Raschka\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.8.12\n",
      "IPython version      : 8.0.1\n",
      "\n",
      "torch            : 1.10.1\n",
      "pytorch_lightning: 1.5.10\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a 'Sebastian Raschka' -v -p torch,pytorch_lightning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Baseline -- Convolutional Neural Network on MNIST"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import time\n",
    "\n",
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    torch.backends.cudnn.deterministic = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "##########################\n",
    "### SETTINGS\n",
    "##########################\n",
    "\n",
    "# Hyperparameters\n",
    "RANDOM_SEED = 1\n",
    "LEARNING_RATE = 0.001\n",
    "NUM_EPOCHS = 10\n",
    "BATCH_SIZE = 128\n",
    "\n",
    "# Architecture\n",
    "NUM_CLASSES = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install gitpython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "from git import Repo\n",
    "\n",
    "if not os.path.exists(\"mnist-pngs\"):\n",
    "    Repo.clone_from(\"https://github.com/rasbt/mnist-pngs\", \"mnist-pngs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision import transforms\n",
    "\n",
    "data_transforms = {\n",
    "    \"train\": transforms.Compose(\n",
    "        [\n",
    "            transforms.Resize(32),\n",
    "            transforms.RandomCrop((28, 28)),\n",
    "            transforms.ToTensor(),\n",
    "            # normalize images to [-1, 1] range\n",
    "            transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),\n",
    "        ]\n",
    "    ),\n",
    "    \"test\": transforms.Compose(\n",
    "        [\n",
    "            transforms.Resize(32),\n",
    "            transforms.CenterCrop((28, 28)),\n",
    "            transforms.ToTensor(),\n",
    "            # normalize images to [-1, 1] range\n",
    "            transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),\n",
    "        ]\n",
    "    ),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data.dataset import random_split\n",
    "from torchvision.datasets import ImageFolder\n",
    "\n",
    "train_dset = ImageFolder(root=\"mnist-pngs/train\", transform=data_transforms[\"train\"])\n",
    "\n",
    "train_dset, valid_dset = random_split(train_dset, lengths=[55000, 5000])\n",
    "\n",
    "test_dset = ImageFolder(root=\"mnist-pngs/test\", transform=data_transforms[\"test\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "\n",
    "train_loader = DataLoader(\n",
    "    dataset=train_dset,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    drop_last=True,\n",
    "    num_workers=4,\n",
    "    shuffle=True,\n",
    ")\n",
    "\n",
    "valid_loader = DataLoader(\n",
    "    dataset=valid_dset,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    drop_last=False,\n",
    "    num_workers=4,\n",
    "    shuffle=False,\n",
    ")\n",
    "\n",
    "test_loader = DataLoader(\n",
    "    dataset=test_dset,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    drop_last=False,\n",
    "    num_workers=4,\n",
    "    shuffle=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import torchvision.utils as vutils\n",
    "\n",
    "real_batch = next(iter(train_loader))\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.axis(\"off\")\n",
    "plt.title(\"Training images\")\n",
    "plt.imshow(\n",
    "    np.transpose(\n",
    "        vutils.make_grid(real_batch[0][:64], padding=2, normalize=True), (1, 2, 0)\n",
    "    )\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "\n",
    "class PyTorchCNN(torch.nn.Module):\n",
    "    def __init__(self, num_classes):\n",
    "        super().__init__()\n",
    "\n",
    "        self.num_classes = num_classes\n",
    "        self.features = torch.nn.Sequential(\n",
    "            torch.nn.Conv2d(\n",
    "                in_channels=3,\n",
    "                out_channels=8,\n",
    "                kernel_size=(3, 3),\n",
    "                stride=(1, 1),\n",
    "                padding=1,\n",
    "            ),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2), padding=0),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.Conv2d(\n",
    "                in_channels=8,\n",
    "                out_channels=16,\n",
    "                kernel_size=(3, 3),\n",
    "                stride=(1, 1),\n",
    "                padding=1,\n",
    "            ),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2), padding=0),\n",
    "        )\n",
    "\n",
    "        self.classifier = torch.nn.Sequential(\n",
    "            torch.nn.Flatten(),\n",
    "            torch.nn.Linear(784, 128),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.Linear(128, num_classes),\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.features(x)\n",
    "        x = self.classifier(x)\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pytorch_lightning as pl\n",
    "import torchmetrics\n",
    "\n",
    "\n",
    "# LightningModule that receives a PyTorch model as input\n",
    "class LightningModel(pl.LightningModule):\n",
    "    def __init__(self, model, learning_rate):\n",
    "        super().__init__()\n",
    "\n",
    "        self.learning_rate = learning_rate\n",
    "        # The inherited PyTorch module\n",
    "        self.model = model\n",
    "\n",
    "        # Save settings and hyperparameters to the log directory\n",
    "        # but skip the model parameters\n",
    "        self.save_hyperparameters(ignore=[\"model\"])\n",
    "\n",
    "        # Set up attributes for computing the accuracy\n",
    "        self.train_acc = torchmetrics.Accuracy()\n",
    "        self.valid_acc = torchmetrics.Accuracy()\n",
    "        self.test_acc = torchmetrics.Accuracy()\n",
    "\n",
    "    # Defining the forward method is only necessary\n",
    "    # if you want to use a Trainer's .predict() method (optional)\n",
    "    def forward(self, x):\n",
    "        return self.model(x)\n",
    "\n",
    "    # A common forward step to compute the loss and labels\n",
    "    # this is used for training, validation, and testing below\n",
    "    def _shared_step(self, batch):\n",
    "        features, true_labels = batch\n",
    "        logits = self(features)\n",
    "        loss = torch.nn.functional.cross_entropy(logits, true_labels)\n",
    "        predicted_labels = torch.argmax(logits, dim=1)\n",
    "\n",
    "        return loss, true_labels, predicted_labels\n",
    "\n",
    "    def training_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "        self.log(\"train_loss\", loss)\n",
    "\n",
    "        # To account for Dropout behavior during evaluation\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            _, true_labels, predicted_labels = self._shared_step(batch)\n",
    "        self.train_acc.update(predicted_labels, true_labels)\n",
    "        self.log(\"train_acc\", self.train_acc, on_epoch=True, on_step=False)\n",
    "        self.model.train()\n",
    "        return loss  # this is passed to the optimzer for training\n",
    "\n",
    "    def validation_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "        self.log(\"valid_loss\", loss)\n",
    "        self.valid_acc(predicted_labels, true_labels)\n",
    "        self.log(\n",
    "            \"valid_acc\", self.valid_acc, on_epoch=True, on_step=False, prog_bar=True\n",
    "        )\n",
    "\n",
    "    def test_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "        self.test_acc(predicted_labels, true_labels)\n",
    "        self.log(\"test_acc\", self.test_acc, on_epoch=True, on_step=False)\n",
    "\n",
    "    def configure_optimizers(self):\n",
    "        optimizer = torch.optim.Adam(self.parameters(), lr=self.learning_rate)\n",
    "        return optimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pytorch_lightning.callbacks import ModelCheckpoint\n",
    "from pytorch_lightning.loggers import CSVLogger\n",
    "\n",
    "torch.manual_seed(RANDOM_SEED)\n",
    "pytorch_model = PyTorchCNN(num_classes=NUM_CLASSES)\n",
    "\n",
    "lightning_model = LightningModel(model=pytorch_model, learning_rate=LEARNING_RATE)\n",
    "\n",
    "callbacks = [\n",
    "    ModelCheckpoint(save_top_k=1, mode=\"max\", monitor=\"valid_acc\"),  # save top 1 model\n",
    "    pl.callbacks.progress.TQDMProgressBar(refresh_rate=50),\n",
    "]\n",
    "\n",
    "logger = CSVLogger(save_dir=\"logs/\", name=\"my-model\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name      | Type       | Params\n",
      "-----------------------------------------\n",
      "0 | model     | PyTorchCNN | 103 K \n",
      "1 | train_acc | Accuracy   | 0     \n",
      "2 | valid_acc | Accuracy   | 0     \n",
      "3 | test_acc  | Accuracy   | 0     \n",
      "-----------------------------------------\n",
      "103 K     Trainable params\n",
      "0         Non-trainable params\n",
      "103 K     Total params\n",
      "0.413     Total estimated model params size (MB)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation sanity check: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6dd4d92ced0445a791f6979efbad3079",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Training: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training took 2.00 min in total.\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "trainer = pl.Trainer(\n",
    "    max_epochs=NUM_EPOCHS,\n",
    "    callbacks=callbacks,\n",
    "    accelerator=\"auto\",  # Uses GPUs or TPUs if available\n",
    "    devices=\"auto\",  # Uses all available GPUs/TPUs if applicable\n",
    "    logger=logger,\n",
    "    log_every_n_steps=100,\n",
    ")\n",
    "\n",
    "start_time = time.time()\n",
    "trainer.fit(\n",
    "    model=lightning_model, train_dataloaders=train_loader, val_dataloaders=valid_loader\n",
    ")\n",
    "\n",
    "runtime = (time.time() - start_time) / 60\n",
    "print(f\"Training took {runtime:.2f} min in total.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Epoch', ylabel='ACC'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0drjqX3vm242y2sZ2nn7rAM+8fZATrV3ML8zixzeUcc2CqdavYIyJyBJEvBzfD8+sgmP74Jr/D5beFpPT7DjUwC82VfP7bTX4g8oVcwu49ZIZLJsxARkPU1oaY4bMEkQ8VL8Bz33Jef+l/99pWoqiQFB5dXctv9hUzTvVx0lPdvGF5dNZfXEx0yemR/VcxpixyxLEcHv3SdjwDZhwHty4DiacG7VDN3f4+c27Hp568wAfHmulMCeN7149l79fOo3stNg0XRljxi5LEMMl0AV/+DZs/hnMvBKu/zmkZkfl0N4TrfznmwdYt9lDU7uf88/J4ZufmMMnSgpsDCRjzJBZghgOrcfhN7dA9etw4T1wxT9DguusD7vlwxM8uamal3YcRkS4esEUvnxxMYvOyT37mI0x454liFirex9+fQM0eOG6f4dFEafWHrCuQJCXdhzhyU3VVHp8ZKUmcvul53LzhcX2UJsxJqosQcTSB6/C+i9DYjLc/DtnQp0hamjt4tebD/L0mweoaWineKKbf76uhOvPLxq2uZmNMeOLXVliQRX++ji88l2YVAKffwZyhvZkcnV9C//xl2rWb/HS2hngwnMn8s/XzefyOZNsvmZjTExZgog2fyf899dg6y9hzqfgs/8HUjIGdQhV5a39x3hyUzWv7TlKUkIC15ZN5cuXFFMyNTod28YYcyaWIKKppR6evQkOvgmXfhPKvz2o4TI6/AF+V3WYJzdVs+twIxPSk7n3so/wxQunMynThtY2xgwvSxDRcmQH/Prz0HIUrv8FLFg5qN0b27u45tE/4znexqyCDP7t+gVct7CQ1KSzv9vJGGOGwhJENOz5b/iv2yElE1ZvgMLFgz7E5urjeI638T9XlvK5xUU2DIYxJu4sQZwNVdj0MLz2A5i6CFY9A1lThnSoKo8PV4LwqdIplhyMMSOCJYih6mqDF++F7b+B+Svhup9C0tCfQ9jq8TGrIBN3sv1JjDEjQ0zHYRCRq0Rkr4jsE5EHIqzPFZEXRGSbiLwjIvPD1uWIyHoR2SMiu0XkwljGOihNR+Cpa5zkcPn3nGEzziI5qCpVHh8Lp9kdSsaYkSNmX1dFxAU8BlwBeIHNIvKiqoZPR/MdoFJVPysic0LbrwitewT4g6quFJFkwB2rWAelZiv8+kZob4AbfgVzrz3rQ1bXt9DY7mfhtJyzj88YY6IkljWIZcA+Vd2vqp3AOuC6PtvMA14DUNU9QLGIFIhIFnAp8IvQuk5V9cUw1oHZ8Tw8+UlnHKVbX45KcgCo8voAKLMEYYwZQWLZ4F0IeMI+e4HlfbapAv4O2CQiy4DpQBEQAOqA/xCRMmALcJ+qtvQ9iYjcAdwBUFBQQEVFxZCCbW5uPv2+GqT4wK8p/vA5GrLmsqPkAbr2HIM9QztXX7/f1UGKC2p2b+HInvh3UPdbFuOQlUdvVh49xnpZxDJBRLrSaZ/PDwGPiEglsB3YCviBJOB84F5VfVtEHgEeAL53ygFV1wBrAJYsWaLl5eVDCraiooKI+3a2wAv/D3z4O1j4RbI/9TAXJ6YM6Ryn8+Odf2HhOQlcftnI6GY5bVmMU1YevVl59BjrZRHLBOEFpoV9LgJqwjdQ1UZgNYA493ZWh15uwKuqb4c2XY+TIIaXzwPrPg+1O+HKH8KFd0OUb0Ht8AfYXdPI6ouLo3pcY4w5W7FMEJuBmSIyAzgErAJuDN9ARHKA1lAfxW3AG6Gk0SgiHhGZrap7cTqudzGcDr4Nz34B/B1w43Mw84qYnGb34SY6A0HroDbGjDgxSxCq6heRe4CXARfwpKruFJE7Q+ufAOYCT4tIACcB3Bp2iHuBtaE7mPYTqmkMi8pn4Hf3QVYh3PLfkD87Zqeq8vgA66A2xow8MX0qS1U3ABv6LHsi7P1bwMzT7FsJLIllfKcIBuDVf4I3H4UZl8Ln/hPcE2J6ykqPj0mZKUzJtsH4jDEjiz22G+LytzqD7X3wMiy9Da56CFxJMT9vlcdH2bQcG17DGDPiWIIAOF7N+e99E9pq4OofwbLbh+W0Da1d7K9v4frFRcNyPmOMGQxLEK3H4ecrSO7sgJtegHM/Nmyn7n5AzjqojTEjkSUI9wS47Du8V5fO8mFMDuA0L4nAgiIbg8kYM/LEdLC+UWPpbbS5hzZM99mo9Pg4Lz+DrNTY93UYY8xgWYKIE1WlyuujrCgn3qEYY0xEliDixHuijfrmThaekxPvUIwxJiJLEHFysoPaahDGmBHKEkScVB70kZyYwJwpmfEOxRhjIrIEESdVXh/zp2aR5LI/gTFmZLKrUxz4A0G2H2qw8ZeMMSOaJYg42FvbRHuXjeBqjBnZLEHEQZWnAbAnqI0xI5sliDio9Jwg153EORPc8Q7FGGNOyxJEHFR5GmwEV2PMiGcJYpg1d/h5/2iTNS8ZY0Y8SxDDbLu3AVWbQc4YM/JZghhm3U9Q2xhMxpiRzhLEMKs86GP6RDcT0pPjHYoxxvTLEsQwsxFcjTGjhSWIYVTb2M7hhnbroDbGjAqWIIZRpccHWAe1MWZ0iGmCEJGrRGSviOwTkQcirM8VkRdEZJuIvCMi8/usd4nIVhH5fSzjHC6VHh+JCULJ1Kx4h2KMMWcUswQhIi7gMeCTwDzg8yIyr89m3wEqVbUU+BLwSJ/19wG7YxXjcKvy+Jg7JYvUJFe8QzHGmDOKZQ1iGbBPVferaiewDriuzzbzgNcAVHUPUCwiBQAiUgRcA/w8hjEOm2BQ2eZtoGxadrxDMcaYAUmM4bELAU/YZy+wvM82VcDfAZtEZBkwHSgCaoH/DXwT6HdGHRG5A7gDoKCggIqKiiEF29zcPOR9B+JQc5DmDj+pLUeoqDgWs/NEQ6zLYrSx8ujNyqPHWC+LWCaISAMNaZ/PDwGPiEglsB3YCvhF5FPAUVXdIiLl/Z1EVdcAawCWLFmi5eX9bn5aFRUVDHXfgfjNux5gG6uuuICPTBrZs8jFuixGGyuP3qw8eoz1sohlgvAC08I+FwE14RuoaiOwGkCckeuqQ69VwKdF5GogFcgSkV+p6hdjGG9MVXp8ZKYkcm5eRrxDMcaYAYllH8RmYKaIzBCRZJyL/ovhG4hITmgdwG3AG6raqKrfVtUiVS0O7fen0ZwcwHlArnRaNgkJNoKrMWZ0iFmCUFU/cA/wMs6dSM+p6k4RuVNE7gxtNhfYKSJ7cO52ui9W8cRTe1eAPYdtBFdjzOgSyyYmVHUDsKHPsifC3r8FzDzDMSqAihiEN2x21jTgD6oNsWGMGVXsSephUGlTjBpjRiFLEMOg0uNjanYqk7JS4x2KMcYMmCWIYVDl8dn4S8aYUccSRIwda+7g4PFWa14yxow6liBibJvX6X+wGoQxZrSxBBFjWz0+EgQWFNoYTMaY0cUSRIxVeXzMKsgkPSWmdxQbY0zUWYKIIVW1KUaNMaOWJYgY+vBYK77WLhaekxPvUIwxZtAsQcRQldcHYDUIY8yodNoEISL/M2zMpPDlXxWRf4ttWGPD1oM+0pJczCqwEVyNMaNPfzWITxGaZ6GPR3BmejNnUOX1saAwm0SXVdSMMaNPf1cuVdVghIVBIk8GZMJ0+oPsrGm0KUaNMaNWfwmiVUROGWk1tKwtdiGNDXuONNLpD7JwWm68QzHGmCHp7+b8/xd4SUT+BdgSWrYE+DZwf4zjGvWqPD4Aq0EYY0at0yYIVX1JRD4DfAO4N7R4B3C9qm4fhthGta0eH3kZKRTmpMU7FGOMGZLTJggRSQVqVfXmPssniUiqqrbHPLpRrMrjY+G0bJypto0xZvTprw/iUeCjEZZfAfw4NuGMDQ1tXfytrsVGcDXGjGr9JYhLVPX5vgtVdS1waexCGv222wiuxpgxoL8E0V/biN3Y349KzwkASu0JamPMKNbfhf6oiCzruzC0rC52IY1+lZ4Gzs1PJzstKd6hGGPMkPV3m+s3gOdE5Cl63+b6JWBVjOMatVSVSo+PS2fmxTsUY4w5K6etQajqO8BynKamW4Duu5luxkkSJoKahnbqmztsBFdjzKjXb1+Cqtaq6oPAvwD7cZLD94HdAzm4iFwlIntFZJ+IPBBhfa6IvCAi20TkHRGZH1o+TUQ2ishuEdkpIvcN+jeLk5MPyFn/gzFmlOvvOYhZOE1JnweOAc8CoqqXDeTAIuICHsO5LdYLbBaRF1V1V9hm3wEqVfWzIjIntP0KwA/8o6q+JyKZwBYR+WOffUekSo+PZFcCc6dkxTsUY4w5K/3VIPbgXKyvVdVLVPUnQGAQx14G7FPV/araCawDruuzzTzgNQBV3QMUi0iBqh5W1fdCy5twaiyFgzh33FR6fMybmkVyot3oZYwZ3frrpL4epwaxUUT+gHOBH8xjwYWAJ+yzF6dPI1wV8HfAptDdUdOBIqC2ewMRKQYWAW9HOomI3AHcAVBQUEBFRcUgQuzR3Nw85H27BYJK5cFWLi1MPOtjxVM0ymIssfLozcqjx1gvi/7GYnoBeEFE0oHPAF8FCkTkceAFVX3lDMeOlEy0z+eHgEdEpBLYDmzFaV5yDiCSAfwXcL+qNp4mzjWE5q1YsmSJlpeXnyGsyCoqKhjqvt12H26k85U/86kL51O+aFRUeCKKRlmMJVYevVl59BjrZdFfDQIAVW0B1gJrRWQC8DngAeBMCcILTAv7XATU9Dl2I7AaQJxBi6pDL0QkCSc5rI30RPdI1DOCa05c4zDGmGgYVEO5qh5X1f+jqpcPYPPNwEwRmSEiyTjNVS+GbyAiOaF1ALcBb6hqYyhZ/ALYraoPDybGeKr0+MhOS6J4ojveoRhjzFk7Yw1iqFTVLyL3AC8DLuBJVd3ZPc+1qj4BzAWeFpEAsAu4NbT7xcBNwPZQ8xPAd1R1Q6zijYZKj4+yaTk2gqsxZkyIWYIACF3QN/RZ9kTY+7eAU2atU9VNjLJpTVs6/Lxf28SVJZPjHYoxxkSF3YsZJTsONRBUWGgzyBljxghLEFFSaU9QG2PGGEsQUVLl9TFtQhoTM1LiHYoxxkSFJYgoqfI0WO3BGDOmWIKIgqNN7RzytdkUo8aYMcUSRBRUeZwpRi1BGGPGEksQUVDpOYErQZhfaHcwGWPGDksQUVDlaWDO5ExSk1zxDsUYY6LGEsRZCgaVqtAT1MYYM5ZYgjhL++tbaOrwW/+DMWbMsQRxlrpHcLUEYYwZayxBnKVKj4+MlETOy8+IdyjGGBNVliDOUpXXx4LCbFwJo2psQWOMOSNLEGehvSvA7sONLDwnJ96hGGNM1FmCOAu7DjfSFVAbYsMYMyZZgjgLlQd9gHVQG2PGJksQZ6HK62NyViqTs1PjHYoxxkSdJYiz4DwgZ8NrGGPGJksQQ3SipZMDx1pZOC033qEYY0xMWIIYoiqvD8BqEMaYMcsSxBBVenyIwAIbwdUYM0ZZghiiKo+PmZMyyExNincoxhgTEzFNECJylYjsFZF9IvJAhPW5IvKCiGwTkXdEZP5A940nVaXS47PnH4wxY1rMEoSIuIDHgE8C84DPi8i8Ppt9B6hU1VLgS8Ajg9g3bjzH2zjR2mVPUBtjxrRY1iCWAftUdb+qdgLrgOv6bDMPeA1AVfcAxSJSMMB946ayu4PaahDGmDEsMYbHLgQ8YZ+9wPI+21QBfwdsEpFlwHSgaID7AiAidwB3ABQUFFBRUTGkYJubmwe87+93d5CcAEf2vkf9B2NvkL7BlMV4YOXRm5VHj7FeFrFMEJGunNrn80PAIyJSCWwHtgL+Ae7rLFRdA6wBWLJkiZaXlw8p2IqKCga67092v0npNPj45RcN6Vwj3WDKYjyw8ujNyqPHWC+LWCYILzAt7HMRUBO+gao2AqsBRESA6tDLfaZ946UrEGTHoQa+eMH0eIdijDExFcs+iM3ATBGZISLJwCrgxfANRCQntA7gNuCNUNI4477xsvdIEx3+oA3QZ4wZ82JWg1BVv4jcA7wMuIAnVXWniNwZWv8EMBd4WkQCwC7g1v72jVWsg7HVphg1xowTsWxiQlU3ABv6LHsi7P1bwMyB7jsSVHl8TExPpig3Ld6hGGNMTNmT1IPkjOCag9NlYowxY5cliEFoau9iX12zNS8ZY8YFSxCDsN3bgCqUWYIwxowDliAGobuDuqzIRnA1xox9liAGocrjY0ZeOjnu5DNvbIwxo5wliAHqGcHVag/GmPHBEsQAHWls52hTh3VQG2PGDUsQA1TV3f9gCcIYM05YghigrR4fSS5h3tSseIdijDHDwhLEAFV5fMybkkVKoiveoRhjzLCwBDEAgaCy3dtgzUvGmHHFEsQA7DvaTEtnwDqojTHjiiWIAaj0nACsg9oYM75YghiASk8DWamJzJiYHu9QjDFm2FiCGIDuEVwTEmwEV2PM+GEJ4gzaOgPsrW2y/gdjzLhjCeIMdtQ0EAgqZUU58Q7FGGOGlSWIM6g86AOsg9oYM/5YgjiDSq+Pwpw08jNT4h2KMcYMK0sQZ1B50Gf9D8aYcckSRD/qmjo45GuzBGGMGZcsQfRjm9cHWP+DMWZ8sgTRj0qPD1eCML/QRnA1xow/ibE8uIhcBTwCuICfq+pDfdZnA78CzgnF8iNV/Y/Quq8CtwEKbAdWq2p7LOPtq9LjY1ZBJu7kmBaTMeYMurq68Hq9tLcP6yXgjLKzs9m9e3e8wxiQ1NRUioqKSEpKGvA+MbvyiYgLeAy4AvACm0XkRVXdFbbZ3cAuVb1WRPKBvSKyFsgHvgLMU9U2EXkOWAU8Fat4+woGlSqPj2tKpwzXKY0xp+H1esnMzKS4uBiRkTOiQVNTE5mZmfEO44xUlWPHjuH1epkxY8aA94tlE9MyYJ+q7lfVTmAdcF2fbRTIFOcvngEcB/yhdYlAmogkAm6gJoaxnuLAsRYa2/3WQW3MCNDe3s7EiRNHVHIYTUSEiRMnDroGFsu2k0LAE/bZCyzvs81PgRdxLv6ZwA2qGgQOiciPgINAG/CKqr4S6SQicgdwB0BBQQEVFRVDCra5ubnXvn851AVA55F9VFTsH9IxR6u+ZTHeWXn0Fo/yyM7Oprm5eVjPORCBQICmpqZ4hzFg7e3tg/rbxTJBREr12ufzJ4BK4HLgPOCPIvJnnD6L64AZgA/4jYh8UVV/dcoBVdcAawCWLFmi5eXlQwq2oqKC8H03/nYH7mQvN15zGa5xNkhf37IY76w8eotHeezevXtENuWMliambqmpqSxatGjA28eyickLTAv7XMSpzUSrgefVsQ+oBuYAHweqVbVOVbuA54GLYhjrKSq9DSwozB53ycEYY7rFMkFsBmaKyAwRScbpZH6xzzYHgRUAIlIAzAb2h5ZfICLuUP/ECmDYbhXo8AfYXdNo/Q/GGAB8Ph///u//Puj9rr76anw+X/QDGiYxa2JSVb+I3AO8jNNk9KSq7hSRO0PrnwB+ADwlIttxmqS+par1QL2IrAfew+m03kqoGWk47D7cRGcgaAnCmBHo+7/bya6axqgec97ULB68tuS067sTxD/8wz/0Wh4IBPo97oYNG6ISX7zE9EE5Vd2gqrNU9TxV/WFo2ROh5ICq1qjqlaq6QFXnh/cxqOqDqjontPwmVe2IZazhKg/aFKPGmB4PPPAAf/vb31i4cCFLly7lsssu48Ybb+SCCy4A4DOf+QyLFy+mpKSENWt6vssWFxdTX1/PgQMHmDt3LrfffjslJSVceeWVtLW1nfZ8P/vZz1i6dCllZWVcf/31tLa2AlBbW8tnP/tZysrKKCsr48033wTg6aefprS0lLKyMm666abo/eKqOmZeixcv1qHauHHjyff3r9uqS//ljxoMBod8vNEsvCyMlUdf8SiPXbt2Dfs5w1VXV2tJSYmqOr+/2+3W/fv3a2Njo6qqHjt2TFVVW1tbtaSkROvr61VVdfr06VpXV6fV1dXqcrl069atqqr6uc99Tn/5y1+e9nzd+6uqfve739VHH31UVVX//u//Xn/84x+rqqrf71efz6c7duzQWbNmaV1dXa9YIolUjsC7epprqg21EUFlaIpRu+faGBPJsmXLej1w9uijj1JWVsYFF1yAx+Phgw8+OGWfGTNmsHDhQgAWL17MgQMHTnv8HTt28NGPfpQFCxawdu1adu7cCcCf/vQn7rrrLgBcLhfZ2dn86U9/YuXKleTl5QEwYcKEKP2WNhbTKXytnVTXt1j/gzHmtNLT00++r6io4NVXX+Wtt96iqqqKRYsWRXwgLSWlZ04Zl8uF3+8/ZZtut9xyCz/96U/Zvn07Dz74YL8PuKlqzL7MWoLoY5u3AcAShDHmpMzMzNM+ENfQ0EBubi5ut5s9e/bw17/+9azP19TUxJQpU+jq6mLt2rUnl69YsYLHH38ccDrIGxsbWbFiBc899xzHjh0D4Pjx42d9/m6WIPqo9PgQgQVF2fEOxRgzQkycOJGLL76Y+fPn841vfKPXuquuugq/309paSnf+973TnZcn40f/OAHLF++nCuuuII5c+acXP7II4+wceNGFixYwOLFi9m5cyclJSV897vf5WMf+xhlZWV87WtfO+vzd7NhSvuo8vg4Lz+DrNSBj3hojBn7nnnmmYjLU1JSeOmllyKu6+5nyMvLY8eOHSeXf/3rX+/3XHfdddfJvoZwBQUF/Pa3vz1l+c0338zNN9/c7zGHwmoQYVTV6aAuyol3KMYYE3dWgwjjPdHGsZZOFp6TE+9QjDHjwN13381f/vKXXsvuu+8+Vq9eHaeIerMEEabS4wNgodUgjDHD4LHHHot3CP2yJqYwVR4fyYkJzJkyekZnNMaYWLEEEabK62P+1CySXFYsxhhjV8IQf1DZfqjBxl8yxpgQSxAhh5qDtHfZCK7GGNPNEkTIfl8QsCeojTFnLyMjA4CamhpWrlwZcZvy8nLefffd4Qxr0OwuppD9DUFy3UmcM8Ed71CMMf156QE4sj26x5y8AD75UHSPCUydOpX169dH/bjDxWoQIfsbAjaCqzEmom9961u9ZpT7p3/6J77//e9z7bXXcv7557NgwYKITzgfOHCA+fPnA9DW1saqVasoLS3lhhtu6Hc+CHCepl6yZAklJSU8+OCDJ5dv3ryZiy66iLKyMpYtW0ZTUxOBQICvf/3rLFiwgNLSUn7yk59E5fe2GgTQ3OGnpln5nDUvGTPyxeCb/pmsWrWK+++//+SMcs899xx/+MMfuO222ygsLKS+vp4LLriAT3/606f9kvn444/jdrvZtm0b27Zt4/zzz+/3nD/84Q+ZMGECgUCAFStWsG3bNubMmcMNN9zAs88+y9KlS2lsbCQtLY01a9ZQXV3N1q1bSUxMjNqAfZYggO3eBhSbQc4YE9miRYs4evQoNTU11NXVkZuby5QpU7j77rv561//SkJCAocOHaK2tpbJkydHPMYbb7zBV77yFQBKS0spLS3t95zPPfcca9aswe/3c/jwYXbt2oWIMGXKFJYuXQpAVlYWAK+++ip33nkniYnOJT1ac0JYgqDnCWobg8kYczorV65k/fr1HDlyhFWrVrF27VqOHTvGli1bSEpKori4uN95G4ABN2FXV1fzox/9iM2bN5Obm8stt9xCe3v7aed+iNWcENYHgfME9SS3MCE9Od6hGGNGqFWrVrFu3TrWr1/PypUraWhoIC8vj6SkJDZu3MiHH37Y7/6XXnrpybkdduzYwbZt2067bWNjI+np6WRnZ1NbW3tytNg5c+ZQU1PD5s2bAWfeCL/fz5VXXskTTzxxchIia2KKokqPj3OzLVcaY06vpKSEpqYmCgsLmTJlCl/4whe4+uqrWbJkCQsXLuw1b0Mkd911F6tXr6a0tJSFCxeybNmy025bVlbGokWLKCkp4dxzz+Xiiy8GIDk5mWeffZZ7772XtrY20tLSePXVV7ntttt4//33KS0tJSkpidtvv5177rnnrH/ncZ8gOvwBPjozjwlddfEOxRgzwm3f3nN7bV5eHq+99hqZmaeO3dbc3AxAcXHxyXkg0tLSWLdu3YDP9dRTT0VcvnTp0oiz1j388MM8/PDDAz7+QMT0a7OIXCUie0Vkn4g8EGF9toj8TkSqRGSniKwOW5cjIutFZI+I7BaRC2MRY0qii//1uTIunDruc6UxxvQSs6uiiLiAx4ArAC+wWUReVNVdYZvdDexS1WtFJB/YKyJrVbUTeAT4g6quFJFkwJ5gM8aMOcuXL6ejo6PXsl/+8pcsWLAgThH1iOXX5mXAPlXdDyAi64DrgPAEoUCmON3vGcBxwC8iWcClwC0AoYTRGcNYjTEjXKzu1Im3t99+e1jOo6qD3ieWCaIQ8IR99gLL+2zzU+BFoAbIBG5Q1aCInAvUAf8hImXAFuA+VW3pexIRuQO4A5z5WisqKoYUbHNz85D3HWusLHqz8ugtHuWRkZGB1+slOzt7RCWJQCBAU1NTvMM4I1WloaGBlpaWQf3tYpkgIv0V+6awTwCVwOXAecAfReTPobjOB+5V1bdF5BHgAeB7pxxQdQ2wBmDJkiVaXl4+pGArKioY6r5jjZVFb1YevcWjPLq6uvB6vRw6dGhYz3sm7e3tpKamxjuMAUlNTaWsrIykpKQB7xPLBOEFpoV9LsKpKYRbDTykTt1nn4hUA3OAg4BXVbvrXutxEoQxZhxKSkpixowZ8Q7jFBUVFSxatCjeYcRMLO9i2gzMFJEZoU7mVTjNSeEOAisARKQAmA3sV9UjgEdEZoe2W0HvvgtjjDExFrMahKr6ReQe4GXABTypqjtF5M7Q+ieAHwBPich2nCapb6lqfegQ9wJrQ8llP05twxhjzDCJ6c3/qroB2NBn2RNh72uAK0+zbyWwJJbxGWOMOT0Zyq1PI5WI1AH9D4hyenlA/Rm3Gh+sLHqz8ujNyqPHWCiL6aqaH2nFmEoQZ0NE3lVVq7FgZdGXlUdvVh49xnpZ2Ah1xhhjIrIEYYwxJiJLED3WxDuAEcTKojcrj96sPHqM6bKwPghjjDERWQ3CGGNMRJYgjDHGRDTuE8SZJjUaT0RkmohsDE3QtFNE7ot3TPEmIi4R2Soiv493LPE2XJN4jRYi8tXQ/5MdIvJrERkdo/YNwrhOEGGTGn0SmAd8XkTmxTequPID/6iqc4ELgLvHeXkA3AfsjncQI0T3JF5zgDLGcbmISCHwFWCJqs7HGU5oVXyjir5xnSAIm9QoNClR96RG45KqHlbV90Lvm3AuAIXxjSp+RKQIuAb4ebxjibewSbx+Ac4kXqrqi2tQ8ZcIpIlIIs6Ml31Hqx71xnuCiDSp0bi9IIYTkWJgETA8012NTP8b+CYQjHMcI0H4JF5bReTnIpIe76DiRVUPAT/CGZH6MNCgqq/EN6roG+8JYiCTGo07IpIB/Bdwv6o2xjueeBCRTwFHVXVLvGMZIbon8XpcVRcBLYzjOVpEJBentWEGMBVIF5Evxjeq6BvvCWIgkxqNKyKShJMc1qrq8/GOJ44uBj4tIgdwmh4vF5FfxTekuPJy6iRe58cxnnj7OFCtqnWq2gU8D1wU55iibrwniIFMajRuiDPZ7y+A3ar6cLzjiSdV/baqFqlqMc6/iz+p6pj7hjhQNonXKQ4CF4iIO/T/ZgVjsNM+pvNBjHSnm9QozmHF08XATcB2EakMLftOaF4PY2wSrxBVfVtE1gPv4dz9t5UxOOyGDbVhjDEmovHexGSMMeY0LEEYY4yJyBKEMcaYiCxBGGOMicgShDHGmIgsQRgzCCISEJHKsFfUniYWkWIR2RGt4xlztsb1cxDGDEGbqi6MdxDGDAerQRgTBSJyQET+TUTeCb0+Elo+XUReE5FtoZ/nhJYXiMgLIlIVenUP0+ASkZ+F5hl4RUTS4vZLmXHPEoQxg5PWp4nphrB1jaq6DPgpzkiwhN4/raqlwFrg0dDyR4HXVbUMZ0yj7if4ZwKPqWoJ4AOuj+lvY0w/7ElqYwZBRJpVNSPC8gPA5aq6PzTg4RFVnSgi9cAUVe0KLT+sqnkiUgcUqWpH2DGKgT+q6szQ528BSar6L8PwqxlzCqtBGBM9epr3p9smko6w9wGsn9DEkSUIY6LnhrCfb4Xev0nPVJRfADaF3r8G3AUn573OGq4gjRko+3ZizOCkhY10C84czd23uqaIyNs4X7w+H1r2FeBJEfkGzoxs3SOg3gesEZFbcWoKd+HMTGbMiGF9EMZEQagPYomq1sc7FmOixZqYjDHGRGQ1CGOMMRFZDcIYY0xEliCMMcZEZAnCGGNMRJYgjDHGRGQJwhhjTET/FwKiMDIfZ35vAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "metrics = pd.read_csv(f\"{trainer.logger.log_dir}/metrics.csv\")\n",
    "\n",
    "aggreg_metrics = []\n",
    "agg_col = \"epoch\"\n",
    "for i, dfg in metrics.groupby(agg_col):\n",
    "    agg = dict(dfg.mean())\n",
    "    agg[agg_col] = i\n",
    "    aggreg_metrics.append(agg)\n",
    "\n",
    "df_metrics = pd.DataFrame(aggreg_metrics)\n",
    "df_metrics[[\"train_loss\", \"valid_loss\"]].plot(\n",
    "    grid=True, legend=True, xlabel=\"Epoch\", ylabel=\"Loss\"\n",
    ")\n",
    "df_metrics[[\"train_acc\", \"valid_acc\"]].plot(\n",
    "    grid=True, legend=True, xlabel=\"Epoch\", ylabel=\"ACC\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at logs/my-model/version_0/checkpoints/epoch=8-step=3860.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at logs/my-model/version_0/checkpoints/epoch=8-step=3860.ckpt\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e6c58b4738ca47fea139718f03ec0a7f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "DATALOADER:0 TEST RESULTS\n",
      "{'test_acc': 0.9926000237464905}\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[{'test_acc': 0.9926000237464905}]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=lightning_model, dataloaders=test_loader, ckpt_path=\"best\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy            : 1.22.2\n",
      "torchmetrics     : 0.6.2\n",
      "torchvision      : 0.11.2\n",
      "pandas           : 1.2.5\n",
      "matplotlib       : 3.3.4\n",
      "pytorch_lightning: 1.5.10\n",
      "torch            : 1.10.1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%watermark -iv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "toc": {
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
